RSS02.D13 ​​Introduction to Necessary Condition Analysis (NCA)​

This doctoral course will teach you the fundamentals of Necessary Condition Analysis (NCA) and help you design your first NCA research project. Necessary Condition Analysis is an innovative research method for identifying necessary (but not sufficient) conditions in data sets. Allowing you to separate the "need-to-haves" from the "nice-to-haves", NCA offers compelling practical advice and novel theoretical insights. The course provides a comprehensive introduction to NCA, including its theoretical logic, practical application, relation to other research methods, and research design.

The course is designed for students, researchers, and practitioners who want to understand the fundamentals of NCA and learn how they can effectively use the method in their own research projects.

This unique five-day course combines theoretical discussions with practical assignments. You will learn more about conditional logic and how it changes the way we think about causal relationships. We will teach you how to conduct an NCA with the statistical programming language R and RStudio. You will also learn how to identify and formulate necessary condition hypotheses in your own area of expertise. The course will be interactive and developmental in nature. At the end of the course, you will be able to design your own NCA research project.

You will earn 2ECTS when you complete the attendance and participations requirements of the course. It will also be possible to obtain 2 additional ECTS. To do so, you need to write a short academic paper that correctly uses NCA, including the theoretical development and empirical testing of necessity hypotheses .

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